TY - GEN
T1 - AIGuide
T2 - 22nd International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2020
AU - Troncoso Aldas, Nelson Daniel
AU - Lee, Sooyeon
AU - Lee, Chonghan
AU - Rosson, Mary Beth
AU - Carroll, John M.
AU - Narayanan, Vijaykrishnan
N1 - Funding Information:
We thank our participants with visual impairments for participating in the user study. We thank Daniel Yi, Rachel Bartuska, and Madison Reddie for their assistance in data analysis. This work was supported in part by the NSF Expeditions: Visual Cortex on Silicon CCF 1317560
Publisher Copyright:
© 2020 ACM.
PY - 2020/10/26
Y1 - 2020/10/26
N2 - Locating and grasping objects is a critical task in people's daily lives. For people with visual impairments, this task can be a daily struggle. The support of augmented reality frameworks in smartphones has the potential to overcome the limitations of current object detection applications designed for people with visual impairments. We present AIGuide, a self-contained offline smartphone application that leverages augmented reality technology to help users locate and pick up objects around them. We conducted a user study to validate its effectiveness at providing guidance, compare it to other assistive technology form factors, evaluate the use of multimodal feedback, and provide feedback about the overall experience. Our results show that AIGuide is a promising technology to help people with visual impairments locate and acquire objects in their daily routine.
AB - Locating and grasping objects is a critical task in people's daily lives. For people with visual impairments, this task can be a daily struggle. The support of augmented reality frameworks in smartphones has the potential to overcome the limitations of current object detection applications designed for people with visual impairments. We present AIGuide, a self-contained offline smartphone application that leverages augmented reality technology to help users locate and pick up objects around them. We conducted a user study to validate its effectiveness at providing guidance, compare it to other assistive technology form factors, evaluate the use of multimodal feedback, and provide feedback about the overall experience. Our results show that AIGuide is a promising technology to help people with visual impairments locate and acquire objects in their daily routine.
UR - http://www.scopus.com/inward/record.url?scp=85096957543&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096957543&partnerID=8YFLogxK
U2 - 10.1145/3373625.3417028
DO - 10.1145/3373625.3417028
M3 - Conference contribution
AN - SCOPUS:85096957543
T3 - ASSETS 2020 - 22nd International ACM SIGACCESS Conference on Computers and Accessibility
BT - ASSETS 2020 - 22nd International ACM SIGACCESS Conference on Computers and Accessibility
PB - Association for Computing Machinery, Inc
Y2 - 26 October 2020 through 28 October 2020
ER -